• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.56-58
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• 2013

최근 페이스북이나 트위터와 같은 소셜네트워크 서비스를 포함하여 대용량의 빅데이터에 대한 처리와 분석이 중요한 이슈로 다뤄지고 있으며, 사용자들이 끊임없이 쏟아내는 데이터로 인해서 이러한 데이터들을 어떻게 다룰 것인지, 혹은 어떻게 분석하여 의미 있고, 가치 있는 것으로 가공할 것인지가 중요한 사안으로 여겨지고 있다. 이러한 빅데이터 관리 도구로써 하둡은 빅데이터의 처리와 분석에 있어서 가장 해결에 근접한 도구로 평가받고 있다. 이 논문은 하둡의 주요 구성요소인 HDFS(Hadoop Distributed File System)와 JAVA에 기반하여 제작되는 온라인 대용량 저장소 시스템의 가장 기본적인 요소인 온라인 데이터 저장소를 직접 설계하고 제작하고, 구현하여 봄으로써 대용량 저장소의 구현 방식에 대한 이슈를 다뤄보도록 한다.

• Journal of Digital Convergence
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• v.14 no.10
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• pp.137-145
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• 2016

The explosive growth of social networking services based on smart devices popularize these relationships and activities online in accordance with the far larger impact of this on the real life offline, the interest and importance for the online activity is increasing. In this study, factors affecting the SNS activity are defined by object, user, influence direction, influence distance and proposed a method to measure organic terms in effect between the SNS users. Influence Direction and Influence Strength (or Distance) are elaborated by using the existing influence measurement element such as structured data - the number of friends, the difference between the number of contacts - and the new influence measurement element such as unstructured data - gap between the former time and the latter time, preference and type of response behavior - that occur in social network service. In addition, the system for collecting and analysing data for measuring influence from social network service and the process model on the method for measuring influence is tested by using sample data on Facebook and explained the implementation probability.

• Journal of Internet Computing and Services
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• v.16 no.1
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• pp.83-90
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• 2015

This paper examines the rising value of social networked journalism and analyzes the case of a social news site based on the theory of networked journalism. Social networked journalism allows the public to be involved in every aspect of journalism production through crowd-sourcing and interactivity. The networking effect with the public is driving journalism to transform into a more open, more networked and more responsive venue. "wikitree" is a social networking news service on which anybody can write news and disseminate it via Facebook and Twitter. It is operated as an open sourced program which incorporates "Google Translate" to automatically convert all its content, enabling any global citizen with an Internet access to contribute news production and share either their own creative contents or generated contents from other sources. Since its inception, "wikitree global" site has been expanding its coverage rapidly with access points arising from 160 countries. Analyzing its international coverage by country and by news category as well as by the unique visit numbers via SNS, the results of the case study imply that networking with the global public can enhance news traffic to the social news site as well as to specific news items. The results also suggest that the utilization of Twitter and Facebook in social networked journalism can break the boundary between local and global public by extending news-gathering ability while growing audience's interest in the site, and engender a feasible business model for a local online journalism.

• Proceedings of the Korea Contents Association Conference
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• 2018.05a
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• pp.345-346
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• 2018

소셜 네트워크 서비스의 사용량이 폭발적으로 증가함에 따라 실생활에서 발생한 이벤트에 관한 정보가 온라인을 통해 급속도로 확산되고 있다. 이에 따라 소셜 데이터를 통해 이벤트를 검출하기 위한 연구들이 진행되고 있다. 본 논문에서는 소셜 데이터를 이용하여 키워드 그래프를 구축하여 사용자 관심도를 고려한 이벤트 검출 기법을 제안한다. 사용자의 소셜 행위로부터 관심도를 계산하고 관심도의 변화를 고려하여 이벤트 판별에 이용한다. 기존의 기법과 달리 관심도를 반영함으로써 결과의 신뢰성을 향상시킨다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.5
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• pp.410-415
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• 2013

Recently, as Internet enters WEB 2.0, many social network services through such as Facebook, Twitter and Youtube appeared. In these social network sites, users can easily make friends, join groups and access others personal information. Therefore, a malicious user can easily gather information of others. In order to protect user's personal information from the unauthenticated users, we propose privacy protection mechanism based on key assignment and user's trust level. A master-key is generated for each users and is segmented into a core-key and several sub-key. The master-key stores at the information owner's side and the sub-key will be distributed to requestor according to the relation and trust level. At last, in order to proof the efficiency, the performance of our proposed mechanism is compared with those of existing mechanisms.

• Informatization Policy
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• v.20 no.2
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• pp.73-90
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• 2013

Rational debate and public conversation in the public sphere of social network are crucial conditions for realizing deliberative democracy. However, negative communication can occur online more frequently than in the real space, and mutually hostile messages are appearing. In the electoral process, citizens combining for particular candidates have made personal attacks against, abused and slandered the opposing candidates. Then, how and to what degree has the flaming behavior been appearing in the elections? Are there influencers to propagate the flaming behavior? And how flaming are these influencers, compared to internet users? This research focuses on the flaming behavior which occurred during the reelection for Seoul Mayor, in order to diagnose the role of social network as an online public sphere. This study analyzes the spreading degree of flaming messages depending on each issue, and the differences of messages between influencers and normal users. There was frequent flaming behaviors to distribute biased information which criticized, laughed at and maliciously attacked individual candidates. Moreover, influencers who advanced leading opinions, displayed a higher flaming degree than normal users.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.5
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• pp.257-266
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• 2017

Two remarkable problems of recent online social network are information overflow and information overload. Since the mid-1990s, many researches to overcome these issues have been conducted with information recommender systems and context awareness based personalization techniques, the importance of trust or relationship between users to discover influential information has been increasing as recent online social networks become huge. But almost researches have not regarded trust or relationship in real world while reflecting them in online world. In this paper, we present a novel method how to discover influential and spreadable information that is highly personalized to a user. This valuable information is extracted from an information set that consists of lots of information user missed in the past, and we assumes important information is likely to exist in this set.

• The Journal of the Korea Contents Association
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• v.10 no.12
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• pp.137-145
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• 2010

Humans are social existences who connect with others and live together. Communication between human has evolved into diverse formats and contents beyond time and space. Social Network Service builds social relationship based on web and its users increase rapidly in a global environment due to the user-friendly web circumstances, easy access and wide-spread supply of the smart phones. One of the aspect that is taking the center of Social Network Service is a Social Game. Social Games are based on web that has simple rules to play in fictional time and space background. This research is to analyze the relationship between social game, Social Network and user behavior through the Social Games Farm Villand Cafe World.This paper, firstly, is going to observe the characteristics of people who participate in the two social games 'Farm Ville' and 'Cafe World'. It, then, attempts to analyze individual and social human desires depicted in the games. In the social games, personal perception is revealed through an image of "possession", while one's social activity is displayed by an image of "consumption."

• Journal of the Korea Convergence Society
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• v.5 no.1
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• pp.29-34
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• 2014

It appeared with the development of IT skills to help the social network SNS(Social Network Service) on the online form. Many people around the world and in the business environment changes is the emergence of social networks are bringing. And the rapid development of the idea, but are insignificant for the security threats that are used by many people in many companies, and social network services. In addition, although it is true that this connection is increased from the number of mobile machines to the development of M2M, that is not recognized for that vulnerability. To evaluate and identify vulnerabilities against security threats and countermeasures for the SNS access the social network on the M2M After looking for privacy and in the present.

• Information Systems Review
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• v.24 no.1
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• pp.1-19
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• 2022

Social media-based communication has become crucial part of our personal and official lives. Therefore, it is no surprise that social media sentiment analysis has emerged an important way of detecting potential customers' sentiment trends for all kinds of companies. However, social media sentiment analysis suffers from huge number of sentiment features obtained in the process of conducting the sentiment analysis. In this sense, this study proposes a novel method by using Bayesian Network. In this model MBFS (Markov Blanket-based Feature Selection) is used to reduce the number of sentiment features. To show the validity of our proposed model, we utilized online review data from Yelp, a famous social media about restaurant, bars, beauty salons evaluation and recommendation. We used a number of benchmarking feature selection methods like correlation-based feature selection, information gain, and gain ratio. A number of machine learning classifiers were also used for our validation tasks, like TAN, NBN, Sons & Spouses BN (Bayesian Network), Augmented Markov Blanket. Furthermore, we conducted Bayesian Network-based what-if analysis to see how the knowledge map between target node and related explanatory nodes could yield meaningful glimpse into what is going on in sentiments underlying the target dataset.